The most popular approach is using the Term Frequency-Inverse Document Frequency (TF-IDF) technique. Another representation can be count the number of times each word appears in a document. Then we can represent each sentence or document as a vector with each word represented as 1 for present and 0 for absent from the vocabulary. One of the simplest techniques to numerically represent text is Bag of Words.īag of Words (BOW): We make the list of unique words in the text corpus called vocabulary. How do we encode such data in a way which is ready to be used by the algorithms? The mapping from textual data to real valued vectors is called feature extraction. In text processing, words of the text represent discrete, categorical features. OUT: #NLTK provides several stemmer interfaces like Porter stemmer, #Lancaster Stemmer, Snowball Stemmer from import PorterStemmer porter = PorterStemmer() stems = for t in tokens: stems.append(porter.stem(t)) print(stems) OUT: from rpus import stopwords stop_words = set(stopwords.words(‘english’)) tokens = print(tokens) #using NLTK library, we can do lot of text preprocesing import nltk from nltk.tokenize import word_tokenize #function to split text into word tokens = word_tokenize("The quick brown fox jumps over the lazy dog") nltk.download('stopwords') print(tokens) BeautifulSoup - Library for extracting data from HTML and XML documents.NLTK - The Natural Language ToolKit is one of the best-known and most-used NLP libraries, useful for all sorts of tasks from t tokenization, stemming, tagging, parsing, and beyond.We can use python to do many text preprocessing operations.
For Spam Filtering we may follow all the above steps but may not for language translation problem. Note that not all the steps are mandatory and is based on the application use case. For detailed discussion on Stemming & Lemmatization refer here. Thus stemming & lemmatization help reduce words like ‘studies’, ‘studying’ to a common base form or root word ‘study’. The stemmed form of studies is: studi The stemmed form of studying is: study The lemmatized form of studies is: study The lemmatized form of studying is: study